By Steven L. Tanimoto

ISBN-10: 0716780283

ISBN-13: 9780716780281

Ebook via Tanimoto, S.

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Managing big data using cloud computing is though cost effective, agile and scalable but involves some tradeoffs like possible downtime, data security, herd instinct syndrome, correct assessment of data collection, cost, validity of patterns. It’s not an easy ride and there is a gigantic task ahead to store, process and analyze big data using cloud computing. Before moving to big data using cloud following points should be taken care of • • • • Possible Downtime: Internet is the backbone of cloud computing.

After that, the on-premises option can become the cost-savings winner from an accounting perspective as the capital assets involved depreciate. 24 • 7 R. Vashist Validity of Patterns: The validity of the patterns found after the analysis of big data is another important factor. If the patterns found after analysis are not at all valid then the whole exercise of collecting, storing and analysis of data go in vain which involves effort, time and money. Discussions Big Data, just like Cloud Computing, has become a popular phrase to describe technology and practices that have been in use for many years.

However, cloud computing is the natural platform for storing big data but there are several trade offs to use both Cloud Computing Infrastructure for Massive Data: A Gigantic Task Ahead 25 these technologies in unison. Cloud enables big data processing for enterprises of all sizes by relieving a number of problems, but there is still complexity in extracting the business value from a sea of data. Many big projects are failed due to the lack of understanding of problem associated with big data and cloud computing.

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Elements of Artificial Intelligence: An Introduction Using LISP by Steven L. Tanimoto


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